Perceived physical environmental factors related to ...essay.utwente.nl/60447/1/MA_thesis_M_Bourgondiën.pdf · transport (Cerin, Leslie & Owen, 2009 ). According to Susilo and Maat

MMMMASTERTHESIS PSYCHOLOASTERTHESIS PSYCHOLOASTERTHESIS PSYCHOLOASTERTHESIS PSYCHOLOGYGYGYGY

M. Bourgondiën MSc.

Studentnumber: 0220795

Nijmegen, January 2011

Supervisors TNO: mw. dr. M. de Goede

mw. drs. T. Hof

Supervisors Twente University: mw. dr. L.M.A. Braakman – Jansen

dhr. dr. M. Pieterse

Perceived physical environmental factors related to walking and cycling for transport in rural and urban areas in the Netherlands

1

Perceived physical environmental factors related to walking and cycling for

transport in rural and urban areas in the Netherlands

Abstract

Background: The transport related physical activity levels of people have steadily declined, while the health benefits

from active modes of transport are substantial. Coupled with the negative impact of high volumes of motorized

transportation on environmental air quality, this has led to increased interest in understanding the determinants of

transport related physical activity. The aim of this study was to investigate the association of the perceived physical

environment with bicycling and walking for transport for different areas (rural, suburban and urban), in order to

promote physical activity in a planned and systematic way.

Methods: Participants were surveyed by e-mail. The study included 803 inhabitants of the Netherlands, addressing

walking and cycling behavior and associated perceived physical environmental, personal and social environmental

factors. Logistic regression analyses were used to examine the associations between physical environmental variables

and the two outcomes, stratified for perceived degree of urbanization. Furthermore it was investigated to what extent

this relationship is moderated by age and gender.

Results: Respondents who averaged 42 years of age reported 170 min/week cycling and 93 min/week walking for

transportation. Significantly more people in strong urban areas than in rural areas cycled a lot for transport purposes.

No significant differences between location and walking for transport were found. Aesthetics was associated with

higher levels of cycling for transport for people living in strong urban locations. Besides, functionality and safety

appeared to be important influences of higher levels of cycling for people living in rural locations, in models that

controlled for demographic variables, self efficacy and social support. No associations were found with walking for

transport.

Conclusions: Different physical environmental variables were associated with cycling for transport, but not with

walking for transport. These associations differed between people living in rural, suburban and strong urban settings.

Enhancing these environmental attributes may be effective in promoting resident’s transport-related physical activity.

Keywords: Physical activity; Physical environment; Transportation; Rural; Urban; Walking; Bicycling; Netherlands

Introduction

The physical activity levels of populations of industrialized countries have steadily declined in the last

three decades (World Health Organization, 2002). Our current environment tends to discourage physical

activity: increased car ownership and improvements in roadway infrastructure for the purposes of

automobile use have resulted in significant reductions in the frequency and length of active forms of

transport (Cerin, Leslie & Owen, 2009). According to Susilo and Maat (2007), the trend from urbanization

towards suburbanization also greatly affects the way people travel. The relocation of urban functions from

city cores to suburban development nodes or city outskirts tends to be accompanied by a decline in

cycling and walking.

Many journeys are short and cars, however, are the dominant mode of travel. More than 50 percent of car

trips in Europe cover distances of less than five kilometers (Titze, Stronegger, Janschitz & Oja, 2008). Also

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. | .

in the Netherlands, cars are the dominant mode of travel for short distances. For more than 70 percent of

all trips made by car, the distance is shorter than 3 km (RIVM,2009). These short trips could be walked or

bicycled easily, thereby providing the recommended amount of daily physical activity (recent guidelines

for physical activity recommend that adults accumulate, on most days, 30 minutes or more of moderate-

intensity physical activity, in minimum bouts of around ten minutes (Jacobsen, Racioppi & Rutter, 2009).

In the Netherlands, 44 percent of the population does not meet the Dutch standard for healthy physical

activity (CBS,2008). So, by stimulating transport related physical activity a larger percentage of the Dutch

population will reach this physical activity standard.

Yet physical inactivity is a major contributor to many of the leading causes of death, including obesity and

chronic disease (Lorenc, Brunton, Oliver, Oliver & Oakley, 2008). The prevalence of overweight in the

Netherlands is 53 percent for the Dutch male population and 42 percent for the Dutch female population,

with a further respectively 11 and 12 percent reaching weights defined as obese (CBS, 2009).

Besides, the different significant health benefits of physical activity, encouraging active modes of

transports will give considerable advantages for the environment. Switching from driving to walking or

cycling is important for reducing CO2 emissions (Jacobsen et al., 2009). Especially these short distances by

car are accountable for high fuel consumption and the dispersal of fines into the air. Exactly the dispersal

of these short trips often takes place in the residential area. By this, the effect on the public health is large,

because breathing in pollute fines is unhealthy. Considering the positive effects for the environment and

public health it is very important to promote active ways of transport, like walking and cycling.

A better understanding of the relation between perceived environmental characteristics and walking and

cycling would enable more successful interventions aimed at increasing physical activity. Social ecological

models have increasingly been applied to understand the determinants of physical activity and inactivity

(Pikora, Giles-Corti, Bull, Jamrozik & Donovan, 2003). Ecological models specify that physical

environments, social environments and personal-level attributes may influence health behavior and

physical activity. There is a growing body of evidence showing that characteristics of the physical

environment have a significant influence on the active lifestyle choices of adults (Cerin, Leslie, du Toit,

Owen & Frank, 2007; Duncan & Mummery, 2005; Giles-Corti., Kelty, Zubrick & Vallanueva, 2009; Humpel,

Owen, Iverson, Leslie & Bauman, 2004). As Giles-Corti and Donovan (2002) state: ‘the physical

environment provides cues and opportunities for physical activity’ (p.1794).

Physical activity takes place in different domains, which include household, transportation and leisure.

Sugiyama, Leslie, Giles-Corti and Owen (2009) emphasize that different physical environment settings

have different determinants and stress the importance of examining context specific behaviour measures

and using context specific environmental attributes. Therefore, our primary interest is to determine the

associations between physical environmental variables and walking and cycling for transport, while also

considering personal (self efficacy) and social environmental factors (social influences).

The physical environmental features that emerge as important across multiple studies include ‘safety’,

‘aesthetics’ ‘functionality’ and ‘destination’ (Pikora et al., 2003). The safety feature reflects the need to

provide safe physical environments for people and incorporates two elements of safety: personal safety

(such as presence of lighting) and traffic safety (such as the availability of crossings). Weinstein, Feigley,

3

Pullen, Mann and Redan (1999) found that people who perceive their neighbourhood as unsafe, are less

physically active.

The aesthetic feature refers to a pleasant, relatively quiet, landscaped, well maintained environment

where people will take pleasure (Pikora et al, 2003). Literature shows that people are inclined to

undertake physical activity in aesthetically appealing (interesting and pleasing) environments (King,

Stokols & Talen, 2002). Following Maas, Verheij, Spreeuwenberg and Groenwegen (2008), natural

environments are perceived to be more aesthetically appealing than built-up environments.

The destination feature relates to the availability of community and commercial facilities in

neighbourhoods. Where there are appropriate local destinations, there is an increased chance that people

will walk. Relevant facilities in the neighbourhood include post boxes, parks, schools, shops and transport

facilities such as bus stops and train stations. Access to destinations showed a positive correlation with

walking for transport (Cerin et al., 2007).

Finally, the functional feature relates to the physical attributes of the street and path that reflect the

fundamental structural aspects of the local environment. Factors that influence this feature include the

directness of routes to destinations and path maintenance (Pikora et al., 2003).

The personal factor self efficacy is concerned with people’s belief in their capabilities to perform a specific

action required to attain a desired outcome (Conner & Norman, 2008). In this case, the belief in their

capabilities to walk or cycle for transport. Past research has shown that self efficacy is a relevant and

promising determinant of behaviour change related to the process of becoming and staying physically

active (Stevens, Bakker-van Dijk, De Greef, Lemmink & Rispens, 2001; Troped, Saunders, Pate, Reininger &

Addy, 2003; Duncan & Mummery, 2005).

Subjective norms and social support form the social environmental influences. Subjective norms can be

divided in what significant others think the person should do and what significant others are perceived

doing with respect to the behaviour in question (Ajzen, 2006). Social support takes the form of

encouragement of others to try physical activity behavior. Social support has been found to have small to

moderate effects on maintenance of physical activity (Sherwood & Jeffery, 2000).

Studies about the influence of the physical environment have largely occurred in urban settings. This

while urban and rural physical environments are different. These differences often make findings

obtained in urban settings invalid in rural settings (Moore, Jillcot, Shores, Evenson, Brownson & Novick,

2010). Troped et al. (2003) recommended as option for future research to identify shared and unique

correlates of transportation physical activity in urban, suburban and rural settings. Therefore, this study

distinguishes people who are living in rural, suburbanized and strong urbanized areas when investigating

which factors influence transport related physical activity.

There are a number of urban residential characteristics of Europe. As a means of reducing energy

consumption by transport many European cities have implemented measures to limit urban sprawl and

promote the development of compact urban forms (Susilo & Maat, 2007). European cities tend to have a

high density across space. What counts for Europe, counts even more for the Netherlands: the urban

density across space is considerably higher than in the neighbouring countries. As a result, car ownership

is lower in Europe than in US and more people use public transport and bicycles in Europe than in the US

(Susilo & Maat, 2007). Especially in the Netherlands, there is a strong cycling culture: of the 16 million

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inhabitants more than 13 million people own a bicycle. The Netherlands has a high cycle-density and

many cycle-tracks. Whereas in most countries the bike has a recreational function, the bicycle is pre-

eminently a means of transport in the Netherlands.

This explorative study investigates the assumption that people in urban residents are more physical active

for transport purposes than people living in rural residents. Work in the field of transportation has found

people living in certain types of places walk more for travel (Forsyth, Oakes, Lee & Schmitz, 2009).

Walking is more often seen as convenient in urban areas, and cycling in more rural areas (Lorenc et al.,

2008).

Further, we investigate the assumption that different aspects of the physical environment are important

for different urbanization settings. Since rural areas have low population density, there is higher

likelihood that rural residents will live further from activity areas compared to people who live in strong

urbanized locations. The high availability of facilities (e.g. shops and services) at walking and cycling

distance in urban areas will encourage people to walk or cycle. On the other hand, urban areas are also

often characterized by limited green space, which will not contribute to an interesting and pleasing

physical environment that will encourage people to walk or cycle. In rural areas there is lots of green

space, but people often have to use the car to visit facilities (Maas et al., 2008).

The aim of this study is to investigate whether there is an association between the physical environmental

and the level of physical activity (i.e. both walking and cycling) analyzed for different perceived degrees of

urbanization (i.e. rural, suburban and urban). Furthermore we investigate to what extent this relationship

is moderated by age and gender. This paper focuses on transport-related physical activity, here defined as

cycling and walking done to travel to and from work, to do errands, or to go from place to place (Cerin,

Leslie & Owen, 2009). More specifically, the following research questions will be addressed:

1. Is there a difference in the level of cycling and/or walking for transport between people

living in rural, suburban or urban environments?

2. To what extent is there an association between the perceived physical environment and

cycling and walking for transport for people living in rural, suburban or urban

environments?

3. What is the moderating role of age and gender in the influence of the perceived physical

environment on walking and cycling for transport?

Methods

Study design and participants

A cross sectional survey of Dutch inhabitants aged 17-80 was conducted between August and September

2010. An e-mail with an URL to the webquestionnaire, was sent to different persons. At the same time we

asked the potential respondents to send the e-mail through to other potential participants. A lottery-based

incentive was provided. 1137 people opened the questionnaire, of whom 803 completed the whole

questionnaire (70.6 percent). Of these 803 respondents, 694 respondents walk and cycle, 23 respondents

only walk, 64 respondents only cycle and 22 respondents never walk or cycle (of which three persons due

5

health problems) for transport purposes. We used the data of the 694 respondents who both cycle and

walk for transport for our analysis. The time it took to fill out all the questions was approximately fifteen

minutes.

Figure 1

Conceptual model

Study Measures

Perceived physical environmental, perceived social environmental, personal and demographic data were

examined as potential correlates of transportation related physical activity (i.e. walking and cycling) (see

figure 1). The selection of these variables was based on scientific literature about ecological framework,

behaviour change models, the physical activity determinants literature and the ‘Neighborhood

Environment Walkability Scale’ (Saelens, Sallis, Black & Chen, 2003). Our primary interest was to

determine the associations between physical environmental variables and physical activity (i.e. walking

and cycling), while also considering perceived social environmental, personal and demographic factors

Walking for transport

Cycling for transport

Demographics

Age

Gender

Educational attainment

BMI

Availability car

Health status

Perceived physical

environment

Safety

Aesthetics

Functionality

Destination

Perceived social

environment

Subjective norms

Perceived Degree of

Urbanization

Rural

Suburban

Urban

Social support

Self efficacy

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. | .

and whether these possible relations differ for people living in urban areas compared to people living in

rural areas.

Dependent variables (outcome measures)

Participants reported which destinations they had visited in the past seven days from a list of ten common

destinations. These were: ‘school’, ‘work’, ‘shops and services’, ‘bus/train stop’, ‘family or friends’,

‘restaurant or café’, ‘park’, ‘gym or sport facilities’, ‘health institutions’ or ‘other’. Participants reported by

each visited destination their travel mode (walking, cycling or using any other kind of vehicle) and how

many minutes the trip took to reach that particular destination. We computed the minutes walking and we

computed the minutes cycling separately. The outcome variables of the study were the total weekly

minutes of cycling for transport and the total weekly minutes of walking for transport. Since the

distributions of the variables were highly skewed, they were dichotomized using median split for analyses

(see appendix B).

Independent variables

Demographic characteristics

The survey included questions on age, gender, educational attainment, perceived general health, height,

weight, availability of bicycle, availability of car and postal code. We categorized the level of educational

attainment from nine categories into three categories (low, moderate and high) based on the International

Standard Classification of Education (ISCED, Verweij, 2008).

Perceived general health was self-rated by respondents by replying to the following statement: in general,

would you say that your health is: …. They could respond by one of the following categories: bad,

moderate, average, good, very good.

Combining the height and weight, we generated a BMI index for each respondent. We also included a

dummy variable, indicating whether or not respondents had overweight (BMI > 25). We checked the

normality distribution of the independent variables: the significant values in the Kolmogorov-Smirnov test

indicates a deviation from normality of the independent variables (see appendix C).

Perceived physical environmental attributes

Nineteen items were used to assess the perceived environment for cycling and nineteen items were used

to assess the perceived environment for walking. Based on Pikora et al. (2003), these nineteen items

represented four different categories: ‘safety’, ‘aesthetics’, ‘functionality’ and ‘destination’ and provided

the conceptual framework for the perceived physical environment. The items were assessed on a seven

point Likert Scale ranging from 1 (strongly disagree) to 7 (strongly agree). See appendix A for a full list of

items.

The four factors of the perceived physical environment are formative constructs; the items of the

construct do not necessarily coincide. Instead, together they make up the construct. Therefore, it is not

relevant to check its reliability (Hair, Black, Babin, Anderson & Taham, 2006).

7

Self efficacy

Self-efficacy for performing transport related cycling was assessed with four items using a seven point

Likert scale from ‘very difficult’ to ‘very easy’. Respondents were required to rate how easy or difficult it is

for them to cycle for transport to their most visited destination ‘even when the weather is bad’, ‘when it is

very hot outside’, ‘when you are tired’ and ‘when you feel you don’t have time’. The Cronbach’s alpha for

these four items was .81; indicating a high level of internal consistency. The participants also rated the

same items for walking for transport to their most visited walk destination. The Cronbach’s alpha for the

four items ‘self efficacy walking’ was .88, indicating also a high level of internal consistency.

Social influences

Respondents were asked to rate on a seven point Likert scale (strongly disagree – strongly agree) the

following five items: ‘My friends, family and/or colleagues think that I should cycle’, ‘It is expected of me

that I cycle’, ‘My family, friends and/or colleagues frequently use the cycle for transportation’, ‘Many

people like me cycle to such a destination’ and ‘My family, friends and/or colleagues encourage me to use

the bicycle to go to this destination’. The same items were also used for walking.

The Cronbach’s alpha for the five items ‘social influences cycling’ was .81. The Cronbach’s alpha for the

‘social influences walking’ was .88. They both indicate a high level of internal consistency.

Degree of urbanization

This study distinguished between people who are living in rural, suburban and urban areas in

investigating whether perceived physical environmental factors influence transport related physical

activity. We assessed the degree of urbanization on two ways. First on a subjective manner, by asking how

respondents would classify their own neighborhood: rural, suburbanized or urbanized. Second on an

objective manner, based on the number of addresses per square km by checking the postal code of the

respondents. This is measured at municipal level (rural: <1000 addresses per square km, suburban:

1000-15000 addresses per square km and urban environment: >1500 addresses per square km). This

indicator is widely used in the Netherlands (Maas et al., 2008).

Data analysis

Analyses were carried out using SPSS 15.0 software. Descriptive statistics were used to summarize

characteristics of the respondents and to summarize both the independent variables and the two physical

activity outcomes. Items in each factor were averaged to provide a total score for each independent

variable. This method facilitated comparison across the categories, with all having a final score from one

till seven (see table 3).

For the bivariate analyses, the scores on perceived physical environment perceived social influences and

self efficacy were transformed into categorical variables with three levels: low (a less positive perception

of the environment); moderate; or high (a positive perception of the environment). The cutoff point used

for these levels were those that most closely approximated the tertiles of the distribution. The outcome

measures (cycling and walking) were dichotomized at the median split and analyzed separately. By using

bivariate analyses we could discover possible curvilinear relationships.

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. | .

Pearson’s correlations were used to analyze the associations between the different constructs. We

conducted also analyses with Spearman correlations because there was an indication that the variables

deviated from normality.

Anova analyses were used to find out whether there was a significant difference between the average

distance to the most accessed walking and cycling destination for people living in rural, suburban or urban

areas. Further we conducted an anova analysis to find out whether there was a difference in total cycling

and walking minutes and perceived degree of urbanization.

The bivariate relationships (χ2) between the perceived physical environmental, perceived social

environmental, personal and demographic variables and walking and cycling were analyzed. All variables

with p-values less than .25 in the bivariate χ2 analysis were entered into logistic regression analyses. The

reason for carrying out a logistic regression was that it is robust against violations of normality and

violations of the equal variance-covariance across groups (Hair et al., 2006, p.275).

In the models for cycling for transport purposes, we controlled for age, gender, perceived health status

and the availability of a car. Additionally, in the models for walking for transport purposes, we controlled

for age, educational attainment, perceived health status and the availability of a car.

As we think that the association between perceived physical environment and walking and cycling for

transport differs for people living in rural, suburban and urban environments, all models were stratified

by the perceived degree of urbanization, by means of the split file method. In the logistic regression

analyses we first entered the socio-demographic variables, followed by the perceived physical

environmental variables and third the two variables ‘self efficacy’ and ‘social influences’. Furthermore,

Baranowski, Cullen, Nicklas, Thomson and Baranowski (2003) suggested that as human behaviour is very

complex, the presence of interaction terms seems be likely and these terms should be sought. So we tested

for interaction effects between the perceived physical environment and the demographic variables age

and gender.

To minimize the impact of one respondent or a small group of respondents on our results, we checked for

outliers for the two physical activity outcomes. We exclude eleven respondents who are more than 1000

minutes per week physically active for transport purposes.

Results

Degree of urbanization

This study distinguishes people who are living in rural, suburban and urban areas. When respondents are

classified based on the number of households per square kilometers (objective classification), 162

respondents (19%) live in a rural environment (<1000 addresses per square km), 227 respondents (27%)

in a suburban environment (1000-15000 addresses per square km) and 448 respondents (54%) live in a

strong urban environment (>1500 addresses per square km). When classifying the respondents based on

how they perceive their own neighbourhood; 233 people (31%) live in a rural environment, 242 people

(29%) live in a suburban environment and 331 (40%) live in a urban environment (see table 1).

Considering these differences, respondents perceive themselves as more often living in a rural or

suburban setting while the objective method classifies them more often as a resident of a strong urban

9

environment. As reference in this study, we use the subjective perceive degree of urbanization because we

expect that the subjective classification is more sensitive and so more valid.

Table 1

Respondents (N) classified (Subjective and Objective) as living in Rural, Suburban or Urban areas.

Subjective

Objective

Rural (N) Suburban (N) Urban (N) Total (N) Percentage

(%)

Rural (N) 131 19 12 162 19%

Suburban (N) 95 109 23 227 27%

Urban (N) 38 114 296 448 54%

Total (N) 264 242 331 837 (100)

(%) 31% 29% 40% (100)

Accessed destinations

The most frequently accessed destinations by bicycle are place of work (31%), shops/services (30%),

family, friends (8%), sport clubs (8%), train / bus station (7%), school (6%), cafés/restaurants (3%), park

(2%) and other destinations (4%). The average cycling distance is 4.0 km (Standard deviation (SD) = 4.9

km).

The most frequently accessed walking destinations are shops/services (42%), park (14%), family, friends

(12%), train/bus station (11%), school (3%), cafés/ restaurants (2%), work (2%), sport clubs (2%),

health institutions (1%) and other destinations (11%). The average walking distance is 1.3 km (SD = 1.7

km).

For rural and suburban residents, the most frequently accessed destinations for walking as well as cycling

are shops and services. For residents in an urban area the most frequently accessed destination by bicycle

is work. Shops and services are the most accessed walking destinations (see appendix D).

We notice that when the perceived degree of urbanization increases, the cycling distance to the most

frequently accessed destination also increases. Respondents living in rural environments cycled on

average the fewest kilometers to their most visited destination (3,5 km), compared to suburban

environments (average 3.9 km) and urban environments (average 4.5 km). This is however a non-

significant difference (F= 2,78, df = 2, p =.06).

On the other hand, the walking distance to the most frequently accessed destination decreases when de

degree of urbanization increases: respectively 1.6 km (rural), 1.4 km (suburban) and 1.1 km (urban). This

is a significant difference (F=5,943, df=2, p = 0,003) (see appendix E).

Physical activity for transport

Table 2 shows mean minutes of walking and cycling for transport. On average, survey respondents report

engaging in cycling for transport purposes 170 minutes ± 156 per week with a median value of 130.

Besides they report engaging in walking for transport purposes 93 minutes ± 118 per week with a median

value of 50.

A larger proportion of people living in urban environments are in the higher level group for cycling: 59.1%

urban participants against 37.6% rural participants reporting a high level of transport related cycling

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(χ2=24,20, df=2, p=.000). Participants living in strong urban locations (mean minutes =192) cycle

significantly more minutes for transport than participants living in rural locations (mean minutes =145)

(F=5,93, df=2, p=.003). We found no association between degree of urbanization and walking for transport

(F= 0.198, df=2, p=.821) (see appendix F and G).

Those respondents reporting high values for aesthetics (57,8%; χ2=9,69, df=2, p=.008) and those

reporting a high self efficacy for cycling (59,7%, χ2 =28,17, df =2, p=.000) cycle more minutes for

transport purposes. Remarkably, those respondents reporting a lot of social influences cycle significant

less for transport (54.7%, χ2 =6.97, df =2, p=.031). Respondents who walk more minutes for transport are

found among those with low values for safety (55,5%, χ2=6,09, p=.048) (see appendix H).

Table 2

Mean, median and Standard Deviation (SD) of minutes cycling and walking for transportation for people in rural, suburban en

urban environments.

Demographic characteristics

Table 3 shows the descriptive characteristics of the respondents. The mean age of women in the sample is

37 (SD=13.6) and the mean age of men of the sample is 47 (SD=14.1). The participants are overall a

relatively healthy group; 91 percent of the respondents define their health as good or very good. 99.5

percent of the respondents have a bicycle of which 1.6 percent has an electric bicycle.

There are no significant differences between age and transportation related physical activity (cycling:

χ2=8,34, df=6, p=.214; walking: χ2=8,77, df=6, p=.187). Neither a significant association is found between

BMI > 25 and cycling or walking for transport (χ2 = 1,13, df=1, p=.288; χ2=0,07, df=1, p=.788). A

significant difference between men and women is found for cycling, but not for walking: the proportion of

men (55.8%) who are in the higher level group for cycling are significant larger than the proportion

women (45,1%, χ2=7,84, df=1, p=.005). Significantly larger proportions of those cycling for transport are

found among those who perceive their general health as very good (58,3 %, χ2=11,14, df=3, p=.011)

compared to people who perceived their general health as moderate. Besides, more people with a low

education (64.2%) are in the higher level group for walking (χ2=6,46, df=2, p=.040). Significantly larger

proportions of those cycling and walking are found among those who never have the availability of a car

(resp. 63,4%, χ2=25,28, df=3, p=.000; 64,6%, χ2=10,25, df=3, p=0.017) (see appendix I).

There are no significant gender differences for place of residence: as much men as women live in rural,

suburban and urban environments (χ2=0,46, df=2, p=.797). The proportion of participants with a high

education living in a strong urban environment (46,5%) is significantly higher than for those with a low

education(16.7%; χ2=30,59, df=4, p=0.000). There is also an association between BMI > 25 and location

Total

N Mean, median (SD)

Rural

N Mean, median,(SD)

Suburban

N Mean, median, (SD)

Urban

N Mean, median, (SD)

Cycling for

transport

734 17170, 130, (156) 229 145, 80, (160) 202 163, 125, (128) 303 192, 165, (156)

Walking for

transport

734 93, 50, (118) 229 89, 50, (118) 202 97, 50, (123) 303 92, 55, (116)

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(χ2=9,57, df=1, p=0.008). Respondents with a BMI higher than 25 (defined as overweight) lives more

often in rural environments (45,8%) than urban environments (32.4%). Further, more young respondents

(<30 years) live in an urban environment (56,8%) against 13.4% of older respondents (>60 years)

(χ2=73,83, df=12 p=.000). Finally, there is a significant difference between availability of a car and

perceived degree of urbanization (χ2 =82,98, df=6, p< 0,001): 77.8% of the rural residents always have a

car available against 47.6% of the urban residents (see appendix J).

Table 3

Demographic characteristics respondents

Rural

N (%)

Suburban

N (%)

Urban

N (%)

Gender

Female

Male

115

98

(54)

(46)

104

97

(52)

(48)

154

127

(55)

(45)

Age (yr)

17 – 20

21 – 30

31 – 40

41 – 50

51 – 60

61 – 70

71 – 80

4

40

23

40

61

41

4

(2)

(19)

(11)

(19)

(29)

(19)

(2)

6

48

33

43

45

24

2

(3)

(24)

(16)

(21)

(22)

(12)

(1)

4

125

53

43

45

11

0

(1)

(45)

(19)

(15)

(16)

(4)

(0)

Education

Low

Moderate

High

27

54

132

(12)

(23)

(56)

18

52

131

(9)

(25)

(64)

9

43

229

(3)

(14)

(75)

Body Mass Index

≤ 25

≥25

110

93

(54)

(46)

119

78

(60)

(40)

184

88

(68)

(32)

Availability of a car

Never

Sometimes

Regularly

Always

8

20

24

182

(3)

(9)

(10)

(78)

13

24

26

143

(6)

(12)

(13)

(70)

62

71

28

146

(20)

(23)

(9)

(48)

Availability of a bicycle

Yes, normal

Yes, electric

Yes, both: normal & electric

No

221

5

7

1

(94)

(2)

(3)

(0)

200

3

2

1

(97)

(2)

(1)

(0)

301

1

3

2

(98)

(0)

(1)

(1)

Health Status

Bad

Moderate

Average

Good

Very good

0

4

24

139

46

(0)

(2)

(11)

(65)

(22)

0

2

18

127

54

(0)

(1)

(9)

(63)

(27)

0

4

12

156

109

(0)

(1)

(4)

(56)

(39)

Perceived physical environment

Table 4 shows mean scores on perceived physical environmental categories. For cycling for transport we

found for the different urbanization degrees significant differences in the mean scores aesthetics,

destination and functionality. Participants living in rural areas report significantly more often a high value

of aesthetics in their neighbourhood (41.6%) than participants living in urban locations (29.0%, χ2=16,38,

df=4, p=.003). Besides, they report more often a low value of functionality (42.3%) in their neighbourhood

than participants living in urban locations (31.5%, χ2=9,82, df=4, p=.044).

12

. | .

For walking for transport we found for the different urbanization degrees significant differences in the

mean scores on safety, aesthetics, functionality and destination. Participants living in urbanized areas

report significantly more often a high value of safety (38.2%) than participants living in rural areas

(23.3%, χ2 = 18,55, df=4, p=.001). Besides, participants living in rural locations report significantly more

often a high value of aesthetics in their neighbourhood (47,9%) than participants living in urban locations

(23.3%, χ2 = 56,86, p = .000) and they also report more often a low value of functionality in their

neighbourhood (43.2%) compared to participants living in a urban environment (26.6%, χ2 = 14,43, p =

0.001). Finally, respondents living in strongly urbanized environments report more often a high value of

destinations (54,1%) compared to respondents living in a rural environment (19.2%, χ2 = 84,00, df=4,

p=.000) (see Appendix K).

Table 4

Mean scores on physical environmental attribute categories (7 point Likert Scale: 1 low, 7 high). SD = standard deviation.

Total

N Mean, (SD)

Rural

N Mean, (SD)

Suburban

N Mean, (SD)

Urban

N Mean, (SD)

Cycling

for

transport

Safety 669 4.97 (0.9) 209 4.96 (0.9) 188 4.93 (0.9) 272 5.01 (0.9)

Aesthetics

703 4.47 (1.1) 219 4.73 (1.0) 201 4.41 (1.1) 283 4.30 (1.0)

Destination

747 6.14 (1.2) 234 5.69 (1.4) 206 6.10 (1.2) 307 6.51 (1.0)

Functionality 716 5.42 (1.0) 222 5.33 (1.1) 202 5.43 (1.0) 292 5.48 (0.9)

Walking

for

transport

Safety 663 5.20 (0.9) 206 5.12 (0.8) 182 5.02 (0.9) 275 5.37 (0.9)

Aesthetics

703 4.27 (1.1) 219 4.69 (1.0) 201 4.27 (1.0) 283 3.93 (1.1)

Destination

747 6.14 (1.2) 234 5.69 (1.4) 206 6.10 (1.2) 307 6.51 (1.0)

Functionality 707 5.02 (1.2) 220 4.82 (1.4) 201 4.89 (1.1) 286 5.26 (1.0)

Results correlation analysis

Self efficacy significantly correlates with cycling for transport, for participants living in rural, suburban

and urban environments (respectively: r=0.21, r=0.24 and r=0.21). Furthermore a positive correlation

exists between aesthetics and cycling and walking for transport for people living in urban environments

(r=.12, r=.12). The two dependent variables (walking and cycling for transport purposes) are correlated

for people who live in a rural environment (r = .19), but not for people who live in suburban or urban

environment. There are some significant correlations between the different independent variables.

Although these correlations are significant, the correlations are weak (r<0.3).

As mentioned before, the distributional assumptions are violated. So, we also checked the correlations

with Spearman’s Rho, but no significant different correlations existed (see appendix L and M).

13

Results of the logistic regression analyses

Cycling for transport not stratified for perceived degree of urbanization.

The results of the logistic regression analyses for cycling are shown in table 5. In this model we first

entered the demographic variables (availability of a car, age, gender, perceived general health status and

perceived degree of urbanization: step A). Secondly, we entered the perceived physical environmental

variables (safety, aesthetics, functionality, destination: step B). Third, the social environmental variable

(social influences) and personal variable (self efficacy) were entered (Step C).

Gender is found to be associated with cycling for transport. Women are less likely to cycle for transport

than men. (Odds ratio (OR)=0.65, 95% confidence interval (CI)=0.46 – 0.93, p=.02). Besides, there is a

significant positive association between age and cycling for transport. Older people are more likely to

cycle (OR=1.03, CI=1.01-1.04, p=.001). Availability of a car demonstrate a negative relationship with

cycling for transport purposes (OR=0.63, CI=0.52-0.75, p=.000). People who have always the availability

of a car are less likely to cycle for transport than people who have never or sometimes a car available. The

degree of urbanization is also associated with the likelihood of cycling for transport. People who live in a

rural environment are significantly less likely to cycle for transport than people living in a suburban or

urban environment (OR=1.54, CI=1.23-1.92, p=.000). These associations exist in all three steps (A,B,C).

Besides, perceived general health shows a positive association with the dependent variable, but

disappears when self efficacy and social influences are entered (step C).

Furthermore, people who report a high level of social influences are less likely to cycle for transport

purposes. So, the more encouragement people receive the less likely they cycle. People who report a high

level of self efficacy for cycling are more likely to cycle for transport. This means that people who have

more confidence in cycling, are more likely to cycle for transport compared to people who are less

confident in cycling. After adjusting for self efficacy and social influences (step C), safety shows a negative

relation with cycling for transport. Respondents who perceive their environment as highly safe are less

likely to cycle for transport (OR=0,95, CI=0.91-0.99, p=.013) (see appendix O). Finally, we tested of two

moderators (age and gender) affected the strength of the relationship between the perceived physical

environment variables and cycling for transportation. Age and gender didn’t affect this relationship (see

appendix Q).

Collinearity diagnostics did not suggest that the changes seen in this final model (step C) for

environmental variables (from not statistically significant to significant) could be attributed to collinearity

among these variables (see appendix N). The model explains only small portions of variance. However, the

final model (step A,B,C) does meet the limits of an acceptable fit of .200 (Hair et al., 2006), with a pseudo

R2 of .208. This indicates that other factors, which are not included in this model, influence the likelihood

of cycling for transport purposes.

Cycling for transport stratified for perceived degree of urbanization - rural.

Two demographic variables, age and availability of a car, have a significant effect on cycling for transport

for rural residents in all three steps (A,B,C). Age is positively associated with cycling for transport: older

people are more likely to cycle (OR=1.044, CI=1.01-1.07, p=.002). The availability of a car shows a

14

. | .

negative relationship with cycling for transport (OR=0.48, CI=0.31-0.76, p=.002). Perceived general health

is no longer statistically significant when the two variables social influences en self efficacy are entered

(step C). A positive effect is found for the self efficacy (OR=1.124, CI=1.05-1.21, p=.002). So, people who

have more confidence in cycling are more likely to cycle for transport compared to people who are less

confident in cycling. Social influences shows a negative relation (OR=0.92, CI=0.87–0.97, p=.004). One

physical environment variable, functionality, shows a positive significant effect: rural residents who

perceive their environment as highly functional are more likely to cycle for transport (OR=1.136, CI=1.03-

1.25, p=0.008). And one physical environment variable shows after adjusting for the variables self efficacy

and social influences (step C) a significant effect: rural residents who perceive their environment as highly

safe are less likely to cycle for transport purposes (OR=0.92, CI=0.86-1.0, p=0.036).

The model explains only small portions of variance. However, it does meet the limits of an acceptable fit of

.200 (Hair et al., 2006), with a pseudo R2 of .28. This indicates that other factors, which are not included in

this model, influence the likelihood of cycling for transport for people living in rural areas (see appendix

P).

Cycling for transport stratified for perceived degree of urbanization - suburban.

Also for suburban residents, in all three steps (A,B,C) age is positively associated with cycling for transport

(OR=1.027, CI=1.0-1.06, p=0.053). Gender and the availability of a car show a negative relationship.

Women are less likely to cycle for transport purposes than women (OR = 0.42, CI = 0.21-0.86, p=0.017).

People who always have a car available are less likely to cycle for transport than people who do not have a

car at their disposal (OR = 0.57, CI = 0.38-0.85, p<0.05). Self efficacy shows a positive effect with cycling:

the more confidence people have in cycling for transport the more likely they are going to cycle (OR=1.18,

CI=1.05-1.19, p=.001). The logistic regression model for suburban residents found no perceived

environmental attributes associated with cycling for transport.

The model explains only small portions of variance. However, it does meet the limits of an acceptable fit of

.200 (Hair et al., 2006), with a pseudo R2 of .22. This indicates that other factors, which are not included in

this model, influence the likelihood of cycling for transport for people living in suburbanized areas (see

appendix P).

Cycling for transport stratified for perceived degree of urbanization - urban.

Gender and the availability of a car show a negative relationship with cycling for residents in urban

environments in all three steps. Men are more likely to cycle for transport purposes (OR=0.54, CI=0.26-

0.80, p= .006). People who always have a car available are less likely to cycle for transport than people

who do not have a car at their disposal (OR=0.70, CI=0.55-0.90, p=.006). Besides, perceived general health

shows a positive association with the dependent variable, but disappears when the variables self efficacy

and social influences are entered (step C). One physical environment variable shows a significant effect:

residents living in strong urbanized environments who report a high value of aesthetics are more likely to

cycle for transport purposes (OR=1.07, CI=1.02-1.13, p=.012). Finally, a positive relationship is found for

the self efficacy: people who report a high level of self efficacy are more likely to cycle for transport

(OR=1.10, CI=1.04-1.16, p=.002).

15

The model explains only small portions of variance. It doesn’t meet the limits of an acceptable fit of .200

(Hair et al., 2008), with a pseudo R2 of .192. But the logistic regression model reports still significance

(χ2=41.04, df=10, p=.000) (See appendix P).

Table 5

Odds ratio’s (95%CI) for environmental variables and likelihood of people being high cyclers.

* p < .05

** p < .001

CI = Confidence Interval

Walking for transport not stratified for perceived degree of urbanization.

The results of the logistic regression analyses for walking are shown in table 6. In this model we first

entered the demographic variables (age, educational attainment, perceived degree of urbanization,

perceived general health: step A). Secondly, we entered the perceived physical environmental variables

(safety, aesthetics, functionality, destination: step B). Third, the social environmental variable (social

influences) and personal variable (self efficacy) were entered (Step C).

Only two demographic variables show an association with walking for transport. Availability of car

demonstrates a negative relationship with walking for transport purposes. So, people who always have a

car available are less likely to walk for transport than people who do not have a car at their disposal

(OR=0.80, CI=0.68-0.94, p=.008). Besides, there is a significant positive association between age and

walking for transport: older people are more likely to walk (OR = 1.02, CI = 0.68-0.94, p <0.05). These

associations exist in all three steps (A,B,C) None of the perceived physical environmental variables show

an association with walking for transport (see appendix R).

Total

Odds ratio’s (95% CI)

Rural


Suburban


Urban


Gender 0.65 (0.46-0.93)* 0.68 (0.33-1.42) 0.42 (0.21-0.86)* 0.45 (0.26-0.80)*

Age 1.03 (1.01-1.04)** 1.04 (1.02-1.07)* 1.03 (1.00-1.06)* 1.01 (0.96-1.03)

Availability Car 0.63 (0.52 – 0.75)** 0.48 (0.31-0.76)* 0.57 (0.38-0.85)* 0.70 (0.55-0.90)*

Perceived

degree of

Urbanization

1.54 (1.23 – 1.92)** - - -

Perceived

physical health

1.27 (0.96-1.69) 1.44 (0.81-2.55) 1.18 (0.69 – 2.04) 1,29 (0.81-2.06)

Aesthetics 1.03 (0.99 – 1.06) 0.98 (0.92-1.05) 1.03 (0.96 – 1.09) 1.07 (1.02-1.13)*

Safety 0.95 (0.92 – 0.99)* 0.92 (0.86-1.00)* 0.93 (0.86 – 1.00) 0.98 (0.93-1.05)

Destination 0.99 (0.95 – 1.046) 0.95 (0.87 – 1.03) 1.08 (0.98-1.19) 0.92 (0.81-1.04)

Functionality 1.02 (0.98 – 1.07) 1.14 (1.03-1.25)* 1.04 (0.95-1.15) 0.95 (0.88-1.02)

Self efficacy 1.10 (1.07 – 1.14)** 1.12 (1.05 – 1.21)* 1.12 (1.05-1.19)** 1.10 (1.04-1.16)*

Social influences 0.97 (0.94 – 0.99)* 0.92 (0.87 – 0.97)* 0.98 (0.93-1.03) 0.99 (0.94-1.04)

Nagelkerke’s R2 .28 .28 .22 .19

÷2, p 110.99 (df=11) p=.000 45,41 (df=10), p=.000 33,80 (df =10), p=.000 41.04 (df=10), p=.000

N 655 202 185 268

16

. | .

Finally, we tested of two moderators (age and gender) affected the relationship between perceived

physical environment variables and walking for transportation. Age and gender didn’t affect this

relationship (see appendix T).

These findings on walking for transport purposes need to be viewed with caution as the logistic

regression model reports no significance (χ2 = 18,975, p= .062). Further, the independent variables

explain together only 4% of the total variance. This does not meet the limits of an acceptable fit of .200

(Hair et al., 2008), with a pseudo R2 of 0.038.

Walking for transport stratified for perceived degree of urbanization

The logistic regression model founds that neither perceived environmental attributes nor location (rural,

suburban, strong urban) are associated with walking for transport. So, the logistic regression analyses

stratified for degree of urbanization found neither perceived environmental attributes nor social

environmental, personal variables and demographic variables to be associated with walking for transport

(see appendix S).

Table 6

Odds ratios (95%CI) for environmental variables and likelihood of people being high walkers

* p < 0,05

** p < 0,001

CI = Confidence Interval

Total


Rural


Suburban


Urban


Age 1.02 (1.00-1.03)* 1.02 (1.0-1.04) 1.02 (1.00-1.05) 1.01 (0.99-1,04)

Educational

attainment

0.98 (0.75-1.23) 1.00 (0.65-1.53) 0.88 (0.53-1.46) 1.08 (0.64-1.82)

Availability of a

car

0.80 (0.68-0.94)* 0.83 (0.56-1.25) 0.67 (0.46-0.97) 0.85 (0.69-1.06)

Perceived

degree of

urbanization

0.81 (0.62-1.06) - - -

Perceived

physical health

1.04 (0.84-1.28) 0.80 (0.50-1.23) 0.92 (0.55-1.55) 0.69 (0.44-1.06)

Aesthetics 1.02 (0.98-1.05) 0.99 (0.93-1.06) 1.01 (0.94-1.07) 1.03 (0.99-1.09)

Safety 0.97 (0.94-1.01) 0.98 (0.91-1.06) 0.94 (0.88-1.02) 0.99 (0.93-1.05)

Destination 1.01 (0.97-1.06) 0.98 (0.90-1.05) 0.99 (0.92-1.06) 1.06 (0.96-1.17)

Functionality 0.77 (0.97-1.04) 1.01 (0.95-1.07) 0.99 (0.92-1.06) 1.03 (0.96-1.10)

Self efficacy 1.02 (.099-1.05) 1.05 (1.00-1.11) 1.03 (0.97-1.09) 0.99 (0.94-1.04)

Social influences 0.99 (0.97-1.02) 0.97 (0.93-1.01) 0.99 (0.95-1.03) 1.02 (0.98-1.06)

Nagelkerke’s R2 0.04 .06 .07 .06

÷2, p 18.98 (df=11), p=.062 9.46 (df=10), p=.492 9.88 (df=10), p=.452 13,20 (df=10), p=.213

N 651 200 179 272

17

Discussion

The present study addresses the physical activity level for transport purposes and the influence of the

perceived physical environment on active modes of transport purposes in the Dutch population (17 years

and older).

The reported amount of time spent on cycling and walking for transport purposes by the population in

this study (respectively 170 minutes and 96 minutes weekly on average) is higher than other comparable

studies. Troped et al. (2003) found that English adults spend on average 142 minutes on transport related

physical activity (walking and cycling together) weekly. Van Dyck et al. (2010) conducted a study in a

Belgian population and found on average of 154 minutes walking weekly, including walking for

transportation ànd during leisure time. Humpel et al. (2004) looked at the walking minutes for transport,

and reported an average amount of only 32 minutes of weekly walking to get to and from places by

Australian participants aged > 40.

Participants in our study may have overestimated their total physical activity level. The self reported data

might have been influenced by social desirability. Further, the questionnaire took place in the summer

months. It is more likely that people walk or cycle more for transport in the summer than in the winter

months, due to the better weather circumstances. Further, most respondents in this study had a good or

very good physical general health status (91%) which could also explain the high physical activity level.

The first research question assessed the differences in reported amount of time spent on physical activity

for transport purposes between people living in rural, suburban and strong urban settings. Significant

more people in strong urban regions cycle more minutes per week for transport compared to people in

rural areas. No significant differences exist for walking. This is partly in accordance with the study of

Schutysern and Vienne (2004), where urban residents cycle, but also walk more for transport than people

living in rural or suburban areas.

Ecological models of health behaviour suggest that different environmental attributes may be associated

with different physical activity behaviours. The second research question assessed to what extent there is

an association between the perceived physical environment and cycling for transport and between the

perceived physical environment and walking for transport for people living in a rural, suburban and urban

environment. To date the majority of studies focus on physical active behavior (walking and cycling

together) or on walking for transport alone. Data focusing on the potential determinants of cycling for

transportation are rather scarce.

The key finding of this study is that physical environmental factors are associated with cycling for

transport, whereas physical environmental variables were not related to walking for transport. One

perceived environmental variable (safety) showed a bivariate association with walking for transport, but

in the logistic regression model with age, educational attainment, availability of a car, perceived physical

general health, self efficacy and social influences included, this factor did not contribute significantly with

walking for transport purposes. Neither for rural, nor for suburban and nor for residents living in strong

urban environments. An explanation for this null finding could be that people doesn’t consider walking as

a means of transport. As mentioned before: whereas in most countries the bike has a recreational

function, the bicycle is pre-eminently a means of transport in the Netherlands. Perhaps, people consider a

18

. | .

bicycle as a substitute for a car, but they doesn’t consider walking as an alternative for a car. In line with

our findings for walking for transport purposes, Humpel et al. (2004) also concluded from their study that

no association exists between perceived environmental attributes (accessibility of facilities for walking,

aesthetics, safety, weather) or location (perceiving beach or lake within walking distance) and walking to

get to and from places. Nevertheless, Giles-Corti & Donovan (2002) found that, after adjustment for

demographic variables and motor vehicle ownership, perceiving sidewalks in the neighbourhood, having a

shop with walking distance, and more traffic and busy roads were independently associated with walking

for transport.

It is notable that there is even not a significant relation between self-efficacy and transport related

walking, as self efficacy is documented as a consistent correlate of activity (Sallis & Owen, 2002). Duncan

and Mummery (2005) argues that it is possible that self efficacy does not influence lower intensity

activities such as walking as strongly as it does for higher intensity activities. This may explain its lack of

association in the model examining walking.

In this study, in contrast to walking for transport, three physical environmental factors (functionality,

aesthetics and safety) show statistically significant associations with cycling for transportation. These

associations vary for rural, suburban and urban areas. For residents living in a suburban environment no

physical environmental variables are associated with cycling for transport. However, for rural residents

safety and functionality are associated with cycling. The functional aspect is positively associated with

cycling for transportation: people who find that there is enough space for cycling, the cycling paves are

well maintained, there are shortcuts compared with cars and there are different routes to take, are more

likely to cycle for transport. This finding is congruent with a study of Titze et al (2008). In their study, bike

lane connectivity (‘there are bicycle tracks’; ‘it is possible to take shortcuts with the bicycle compared to

cars’) was positively associated with cycling for transportation. The finding that the functional aspect is

only of influence for cycling for transport for rural residents and not for suburban or urban residents

could be explained by the fact that residents who live in suburban and urban areas perceive their

environment as a highly functional area. This is plausible, because as mentioned before, The Netherlands

have the most cycle tracks of the world, especially in more urbanized areas.

Paradoxically, we found for people living in a rural environment perceived safety was negatively related

to cycling in our study. This counter intuitive relationship could be explained by the fact that those who

spend more time cycling are more aware of a lack of safety (Duncan & Mummory, 2005). This negative

association is in accordance with Humpel et al (2004). The fact that safety did not prove to be an

important influence on cycling for transport for suburban and strong urban residents could be explained

by the participants’ perception of living in a low-crime area.

Our study indicates that for residents living in a strong urbanized environment, aesthetics are associated

with cycling for transport. Those who perceived that they lived in areas with attractive natural and built

features, free from litter with many trees, gardens and green spaces, were more likely to cycle to get to

and from places. This is consistent with previous studies that show the relevance of aesthetically pleasing

environments and physical activity levels. The fact that aesthetics did not prove to be an important

influence on cycling for transport for rural and suburban residents could be explained by the participants’

perception of living all in a highly aesthetical appealing environment. It is possible that there was

19

insufficient variability in perceived environmental characteristics to detect associations with transport

related physical activity.

The third and last research question assessed the moderating role of age and gender in the influence of the

perceived physical environment on walking and cycling for transport. Both age and gender didn’t affect

the (strength of) the relationship between these independent variables and cycling or walking for

transport. In contrast to our study, gender affected the strength of the relationship between the perceived

physical environment variables and cycling in the study of Titze et al. (2008).

Although not the main focus of this study, gender was significantly associated with cycling for residents

living in suburbanized and urbanized areas. The finding that a greater proportion of men than women

were physically active for transport is consistent with other studies (Booth, Owen, Bauman, Clavisi &

Leslie, 2000). This suggests that a stronger emphasis on the needs and interest of women in physical

activity promotion strategies is appropriate. Further, significant positive association of age with cycling

for transport was found as well for rural and suburban residents. It may be that older people perceived

cycling as a more appropriate means of transport. Having high self efficacy was strongly associated with

cycling for transport purposes for people in all types of environment (rural, suburban and strong urban).

Research suggests that self efficacy is important in the initiation and maintenance of physical activity

(Booth et al., 2000; Conner & Norman, 2008). Finally, it is notable that we found a small but significant

negative relationship between social influences and cycling for transport for rural residents. This

association is puzzling because in contrast to our finding, results from Titze et al. (2008) showed that

social support/modeling was positively related with cycling for transport. Similarly, social support from

friends and modeling was positively associated with active transport in a study among Portuguese and

Belgian students (De Bourdeaudhuij, Teixeira, Cardon & Deforche, 2005). It may be that there is some

capitalization on chance, due to multiple testing. Further studies are needed to clarify this issue.

There are several limitations in the present study. First, this study’s cross-sectional design allowed us to

determine whether environmental factors were correlated with activity, but could not be used to

demonstrate that these factors were determinants of transportation activity (i.e. had a causal

relationship). But consistent associations in this and other studies, implies the possibility of a causal

relationship.

Second, we used a self report measure for physical activity which is the most commonly used measure for

assessing physical activity (Maas et al., 2008). Using a self-report measure for physical activity has the

advantage that it is easy to administer and generally acceptable to participants, and can measure a wide

range of values. Yet, self report measures have the disadvantage of incomplete recall and exaggeration of

the amount of activity (due social desirability). In this study we have tried to minimize the disadvantage of

incomplete recall by not simply asking the general amount of minutes that people walk and cycle for

transport purposes. The respondents reported (from a list of ten) the destinations they had visited per

day in the last week, how many minutes the trip took and the transport mode to reach this destination.

Besides, it will not likely that people living in rural environments will exaggerate more or less than people

living in more urbanized environments. So, there will be no bias with relation to degree of urbanization.

Finally, compared to the Dutch population, the sample was more highly educated. Moreover, the

Netherlands have high cycling rates relative to many other countries. These issues may limit the

20

. | .

generalizability of our findings to Netherland and other European countries. On the other hand this study

may provide insights to support cycling in other countries.

The strength of the current study is that it focused on cycling and separately examined walking as active

modes of transport. The reason for this is that different types of active travel behaviours likely have

different determinants, requiring distinct explanatory models (Giles-Corti, Timperio, Bull & Pikora, 2005).

Although the perceived environment had a small, yet significant association with cycling for transport a

recommendation for future studies is the use of both self report as well as objective measurement of the

physical environment. This way, one will be able to analyze whether perceived or objective measures has

the greatest influence of walking and cycling for transportation. The inclusion of objective measures in

future studies would have the advantage of using concrete and absolute measures of the environment,

which could help establish a direct link between physical activity and interventions in the physical

environment to support active living (Lin & Moudon, 2010).

Finally, in order to be able to identify factors of causality, the use of a longitudinal design would be

recommended.

Conclusion

This study indicates that the physical environment can act as a facilitator for a more active lifestyle among

its residents. Although small, the associations identified in this study do add to the body of data on the

influence of perceived environmental attributes on cycling. The differences for rural, suburban and strong

urban residences emphasize that different aspect of the environment may be of differing importance for

different settings. Further this study indicates that different types of physical activity (i.e. walking and

cycling) have different determinants. Promoting a more active lifestyle by improving the physical

environment (safety, aesthetics and functionality) is the key message of this study.

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Appendixes

MMMMASTERTHESIS PSYCHOLOASTERTHESIS PSYCHOLOASTERTHESIS PSYCHOLOASTERTHESIS PSYCHOLOGYGYGYGY

M. Bourgondiën MSc.

Studentnumber: 0220795

Nijmegen, January 2011

Supervisors TNO: mw. dr. M. de Goede

mw. drs. T. Hof

Supervisors Twente University: mw. dr. L.M.A. Braakman – Jansen

dhr. dr. M. Pieterse

1

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Content:

APPENDIX A WEB-SURVEY ................................................................................................................................................................ 2

APPENDIX B NORMALITIES DEPENDENT VARIABLE ................................................................................................................... 12

APPENDIX C NORMALITIES INDEPENDENT VARIABLE ............................................................................................................... 13

APPENDIX D ACCESSED DESTINATIONS ....................................................................................................................................... 18

APPENDIX E ANOVA ANALYSES DISTANCE MOST ACCESSED DESTINATIONS .......................................................................... 19

APPENDIX F Χ2 ANALYSES PERCEIVED DEGREE OF URBANIZATION - DEPENDENT VARIABLE ............................................ 21

APPENDIX G ANOVA ANALYSES PERCEIVED DEGREE OF URBANIZATION - DEPENDENT VARIABLE ................................... 22

APPENDIX H Χ2 ANALYSES INDEPENDENT VARIABLES – DEPENDENT VARIABLES............................................................... 23

APPENDIX I Χ2 ANALYSES DEMOGRAPHIC CHARACTERISTICS – DEPENDENT VARIABLES ................................................... 29

APPENDIX J Χ2 ANALYSES DEMOGRAPHIC VARIABLES – PERCEIVED DEGREE OF URBANIZATION ...................................... 35

APPENDIX K Χ2 ANALYSES PERCEIVED DEGREE OF URBANIZATION - PERCEIVED PHYSICAL ENVIRONMENT VARIABLES39

APPENDIX L CORRELATIONS PEARSON ........................................................................................................................................ 43

APPENDIX M CORRELATIONS SPEARMAN .................................................................................................................................... 45

APPENDIX N COLLINEARITY STATISTICS FOR CYCLING AND WALKING FOR TRANSPORT .................................................... 47

APPENDIX O LOGISTIC REGRESSION ANALYSES CYCLING- NOT STRATIFIED ......................................................................... 48

APPENDIX P LOGISTIC REGRESSION ANALYSES CYCLING- STRATIFIED FOR PERCEIVED DEGREE OF URBANIZATION ..... 51

APPENDIX Q LOGISTIC REGRESSION ANALYSES CYCLING (NOT STRATIFIED) – INTERACTION TERM INCLUDED ............ 59

APPENDIX R LOGISTIC REGRESSION WALKING- NOT STRATIFIED ........................................................................................... 61

APPENDIX S LOGISTIC REGRESSION ANALYSES WALKING- STRATIFIED FOR PERCEIVED DEGREE OF URBANIZATION ... 64

APPENDIX T LOGISTIC REGRESSION ANALYSES CYCLING (NOT STRATIFIED) – INTERACTION TERM INCLUDED ............. 72

APPENDIX U- POPULATION DENSITY PER PROVINCE IN THE NETHERLANDS AND ORIGIN RESPONDENTS ........................ 74

2

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Appendix A Web-survey

Dear participant,

This questionnaire is about walking and cycling for transport purposes. You can think about walking and

cycling to go to stores, your work or to visit your family or friends, for example.

This research is conducted in cooperation with TNO and the Twente University. We are interested in the

factors which influence walking an cycling to get from place to place.

The survey takes about twenty minutes. Please fill in the answers as honest and completely as possible:

there are no good or wrong answers. Your individual responses will be treated completely confidentially

and anonymously. By filling out the survey you will be entered into a drawing to win one of the five 50

euro gift cheques.

Thank you for participating.

The following questions are about your direct neighborhood. This means the surrounding within 5 km

from your home. Please circle the answer that best applies to you.

1. What is your postal code?

2. How would you define your neighbourhood? Non urban – slightly urban – moderately urban – highly urban – very highly urban

3. I can do most of my shopping at local stores (< 5 km) Strongly disagree –disagree – slightly disagree – neutral – slightly agree – agree – strongly agree

4. There are many places to go within easy walking or cycling distance of my home (< 5 km) Strongly disagree –disagree – slightly disagree – neutral – slightly agree – agree – strongly agree

5. It is easy to walk to a transit stop (bus, train, tram) from my home Strongly disagree –disagree – slightly disagree – neutral – slightly agree – agree – strongly agree

Please circle the answer that best applies to you.

6. Are you physically able to cycle for 15 minutes? Yes

No

7. Are you physically able to walk for 15 minutes? Yes

No

8. Do you own a bicycle? (Availability of a bicycle for trips in the city?) Yes, a ‘normal’ bicycle

Yes, an electric bicycle

Yes both, a normal and an electric bicycle

No

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9. Do you own a car? (Availability of a car for trips in the city) Never

Sometimes

Regular

Always

10. Do you ever walk or cycle to reach a destination? You can think to get from house to the

supermarket, your work or to visit family and friends. Yes

No

Which destinations did you visit last week?* Please indicate your destinations per day.

* when your walk and cycle behavior deviates from the normal behavior (i.e. through illness or holiday),

please take a normal weak to answer the questions below.

11. Which destination(s) did you visit last Monday?

(When visit no destination, please click the button ‘further’) School

Work

Stores / facilities (i.e. supermarket, hairdresser)

Train / bus stop

Family / friends / neighbors

Hotel / restaurant / café / place of entertainment

Park

Gym or fitness facilities (i.e. tennis court, swimming pool)

Health institutes (i.e. general practice, pharmacy/drugstore, hospital)

12. A. How much time did you spend on walking from place to place

on Monday (in minutes)?

B. How much time did you spend to bicycle from place to place

on Monday (in minutes)?

C: How much time did you spend traveling in a train, bus, car, tram

or other kind of vehicle on Monday (in minutes)?

13. Which destination(s) did you visit last Tuesday?

When visit no destination, please click the button ‘further’. School

Work


Train / busstop



Park

Gym or fitness facilities (i.e. tennis court, swimmingpool)



Tuesday (in minutes)?


Tuesday (in minutes)?


or other kind of (motor) vehicle Tuesday (in minutes)?

4

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15. Which destination(s) did you visit last Wednesday?


Work


Train / busstop



Park




Wednesday (in minutes)?


Wednesday (in minutes)?


or other kind of (motor) vehicle Wednesday (in minutes)?

17. Which destination(s) did you visit last Thursday?


Work


Train / busstop



Park




Thursday (in minutes)?


Thursday (in minutes)?

C: How much time did you spend travelling in a train, bus, car, tram

or other kind of (motor) vehicle Thursday (in minutes)?

19. Which destination(s) did you visit last Friday?


Work


Train / busstop



Park




Friday (in minutes)?


Friday (in minutes)?


or other kind of (motor) vehicle Friday (in minutes)?

5

. | .

21. Which destination(s) did you visit last Saturday?


Work


Train / busstop



Park




Saturday (in minutes)?


Saturday (in minutes)?


or other kind of (motor) vehicle Saturday (in minutes)?

23. Which destination(s) did you visit last Sunday?


Work


Train / busstop



Park




Sunday (in minutes)?


Sunday (in minutes)?


or other kind of (motor) vehicle Sunday (in minutes)?

The most visited destination within your own neighbourhood.

25. To which destination within your own neighbourhood you cycle most often? (one answer

possible). Please circle the category to which this destination belongs. School

Work

Shop / service

Train / bus station

Family / friends

Cafés / restaurants

Park

Sport clubs

Health institution

Other desintation

No any destination: I don’t cycle (within my neighborhood)

6

. | .

26. To which destination within your own neighbourhood you walk most often? (one answer

possible). Please circle the category to which this destination belongs. School

Work

Shop / service

Train / bus station

Family / friends

Cafés / restaurants

Park

Sport clubs

Health institution

Other desintation

No any destination: I don’t cycle (within my neighborhood)

We are going to look to your most frequently accessed destination by bicycle.

You reported that … is the destination to which you most often cycle. Keep this destination in mind for the

following questions.

27. What is the distance in meters from your home to this destination? (1 km = 1000 meter)

Please circle the answer that best applies to you. How easy or difficult is it for you to cycle to this

destination even when…

28. The weather is bad Very difficult - difficult – slightly difficult – neutral – slightly easy – easy – very easy

29. It is very hot outside Very difficult - difficult – slightly difficult – neutral – slightly easy – easy – very easy

30. You are tired Very difficult - difficult – slightly difficult – neutral – slightly easy – easy – very easy

31. You feel you don’t have time Very difficult - difficult – slightly difficult – neutral – slightly easy – easy – very easy

Please circle the answer that best applies to you. Keep the destination in mind to which you most often

cycle.

32. My family, friends and / or colleagues think that I should cycle to this destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

33. It is expected of me that I cycle to this destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

34. My family, friends and / or colleagues frequently use cycling for transportation to visit such a

destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

7

. | .

35. Many people like me cycle to such a destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

36. My family, friends and / or colleagues encourage me to use the bicycle to this destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

Please circle the answer that best applies to you. Think about your trip to the destination which you have

indicated before. If you bicycle to the destination, how well would the description fit?

37. There is enough space for cycling on the route

Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

38. It is possible to take shortcuts with the bicycle compared to cars Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

39. The places where I cycle along the route are well maintained (paved, even, and not a lot of cracks) Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

40. There are many different routes I can take (I have not to go the same way each time) Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

Please circle the answer that best applies to you. Think about your trip to the destination which you have

indicated before. If you bicycle to the destination, how well would the description fit?

41. I am satisfied with the parking facilities for the bike by this destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

42. Finding a parking place for a car is difficult


We are going to look to your most frequently accessed destination by bicycle.

You reported that … is the destination to which you most often walk. Keep this destination in mind for the

following questions.

43. What is the distance in meters from your home to this destination? (1 km = 1000 meter)

Please circle the answer that best applies to you. How easy or difficult is it for you to walk to this

destination even when…

8

. | .

44. The weather is bad Very difficult - difficult – slightly difficult – neutral – slightly easy – easy – very easy

45. It is very hot outside Very difficult - difficult – slightly difficult – neutral – slightly easy – easy – very easy

46. You are tired Very difficult - difficult – slightly difficult – neutral – slightly easy – easy – very easy

47. You feel you don’t have enough time Very difficult - difficult – slightly difficult – neutral – slightly easy – easy – very easy

Please circle the answer that best applies to you. Keep the destination in mind to which you most

often walk.

48. My family, friends and / or colleagues think that I should walk to this destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

49. It is expected of me that I walk to this destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

50. My family, friends and / or colleagues frequently walk for transportation to visit such a

destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

51. Many people like me walk to such a destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

52. My family, friends and / or colleagues encourage me to walk to this destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

Please circle the answer that best applies to you. Think about your trip to the destination which you

have indicated before. If you walk to the destination, how well would the description fit?

53. There is enough space for walking on the route Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

54. It is possible to take shortcuts walking compared to cars Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

9

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55. The sidewalks along the route are well maintained (paved, even, and not a lot of cracks) Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

56. There are many different routes I can take (I have not to go the same way each time) Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

57. I am satisfied with the parking facilities for the bike by this destination Strongly agree – agree – slightly agree – neutral – slightly disagree – disagree – strongly disagree

58. Finding a parking place for a car is difficult


Please circle the answer that best applies to you, for the cycle destination as well for your walk

destination.

59. There are a lot of trees, gardens, green spaces or parks along the route


’Cycledestionation’

‘Walkdestination’

60. There is a lot of litter on the streets along the route




61. There are attractive buildings / homes along the route




62. There are not many interesting things to look at while walking or cycling to the destination




63. There are many attractive natural sights in my neighborhood (such as landscaping, views)




Please circle the answer that best applies to you, for the cycle destination as well for your walk

destination.

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64. Most drivers exceed the posted speed limits while driving in my neighborhood




65. Crossing busy roads is a big problem along the route




66. There is so much traffic along the route that it makes it difficult or unpleasant to walk or cycle




67. The streets along the route are well lit at night




68. Overall, I feel safe when walking/ cycling along the route




Finally, some questions about your demographic features. Please circle the answer that best applies to

you.

69. What is your gender?

Male

Female

70. What is your age?

71. What is your residence?

72. What is your heighest completed education?

Geen opleiding

Lager onderwijs

Middelbaar algemeen voortgezet onderwijs (MAVO/VMBO)

Hoger algemeen voortgezet onderwijs (HAVO)

Voorbereidend Wetenschappelijk Onderwijs (VWO)

Lager beroepsonderwijs (LBO)

Middelbaar beroepsonderwijs (MBO)

Hoger Beroepsonderwijs (HBO)

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Univeristy

Other, namely

73. In general, my state of health is:

Bad

Moderate

Average

Good

Very good

74. What is your weight (kilograms?)

75. What is your length (in centimeters)?

76. In general, how many days per week are you at least 30 minutes physical

active? Physical active means at least the same effort as walk at a stiff

pace or stiff cycling.

77. Do you have any remarks? Please fill in:

Thanks for your participation

This is the end of the questionnaire. We would like to thank you for your participation.

Please fill in your e-mail address when you would like to have a chance of winning one of the five cheques

to the value of 50 euro. The anonymity will be guaranteed.

E-mail address:

12

. | .

Appendix B Normalities dependent variable

Cycling

Walking

13

. | .

Appendix C Normalities independent variable

Cycling:

Self efficacy cycling

Social influences cycling

Safety cycling

14

. | .

Aesthetics cycling

Functionality cycling

15

. | .

WALKING:

Self efficacy walking

Social influences walking

16

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Safety walking

Aesthetics walking

17

. | .

Functionality walking

Destination

18

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Appendix D Accessed Destinations

School

Work

Shop/service

Train / busstation

Family / friends

Café/ restaurant

Park

Sport club

Health institution

Other destination

Rural cycle destinations: Rural walk destinations:

Suburban Cycle destination s: Suburban walk destinations:

Urban Cycle destinations: Urban walk destinations:

Perceived3categorieën: Rural

Perceived3categorieën: Between

Perceived3categorieën: Between

Perceived3categorieën: Urban Perceived3categorieën: Urban

19

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Appendix E Anova analyses distance most accessed destinations

Cycling:

Distance most accessed cycle destination – perceived degree of urbanization (subjective)

Post Hoc Tests

Distance most accessed cycle destination – degree of urbanization (objective)

Post Hoc Tests

20

. | .

Walking:

Distance most accessed walk destination – perceived degree of urbanization

Post hoc test

Distance most accessed walk cycle destination – degree of urbanization (objective)

Post hoc test

21

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Append ix F χ2 anal yses Perceived d egree of u rbaniz ation - Dep endent variable

Cycling:

Walking

22

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Append ix G Anova anal yses Perceived d egree of u rbaniz ation - Depend ent

variabl e

CYCLING:

WALKING:

23

. | .

Append ix H χ2 analyses Ind epend ent variables – Depend ent variables

Cycling:

Self efficacy cycling * cycling

Social influences cycling * cycling

24

. | .

Safety cycling * Cycling

Aesthetics cycling * Cycling

25

. | .

Functionality cycling * Cycling

Destination * Cycling

26

. | .

Walking:

Self efficacy walking * Walking

Social influences walking * Walking

27

. | .

Safety walking * walking

Aesthetics walking * walking

28

. | .

Functionality walking * walking

Destination * walking

29

. | .

Append ix I χ2 analyses Dem ographic ch aracteristics – Depend ent variabl es

Cycling:

Age categories – cycling

Cycling * Age categories Crosstabulation

Gender - cycling

30

. | .

BMI > 25 - cycling

Educational attainment - cycling

31

. | .

Availability of a car – cycling

Perceived general health - cycling

32

. | .

Walking:

Age categories – walking

Gender - walking

33

. | .

BMI > 25 – walking

Educational attainment - walking

34

. | .

Walking * availability of a car:

Perceived general health - walking

35

. | .

Append ix J χ 2 analyses Dem ographic variables – Perceived degree of

urbaniz ation

Age - Perceived degree of urbanization

*Not fulfilling the condition of Cochran

Age (*fulfilling condition of Cochran) – Perceived degree of urbanization

36

. | .

Gender – Perceived degree of urbanization

Educational attainment - Perceived degree of urbanization

37

. | .

BMI > 25 - Perceived degree of urbanization

Availability of a car – Perceived degree of urbanization

38

. | .

Perceived general health status - Perceived degree of urbanization

39

. | .

Append ix K χ 2 anal yses Perceived d egree of u rbaniz ation - Perceived physical

environm ent variabl es

Cycling:

Safety cycling - Perceived degree of urbanization

Aesthetics cycling - Perceived degree of urbanization

40

. | .

Functionality cycling - Perceived degree of urbanization

Destination - Perceived degree of urbanization

41

. | .

Walking:

Safety walking - Perceived degree of urbanization

Aesthetics walking - Perceived degree of urbanization

42

. | .

Functionality walking - Perceived degree of urbanization

43

. | .

Append ix L Correl ations Pearson

44

. | .

45

. | .

Append ix M C orrel ations Spearm an

46

. | .

47

. | .

Append ix N C oll inearity statistics for C ycl ing and W al king for transp ort

These results are based on a linear regression, which was performed just to obtain the statistics on

collinearity.

Cycling:

Walking:

48

. | .

Append ix O Logistic Regression Analyses Cycling- not stratif ied

Model for cycling with all variables p.25 included

49

. | .

50

. | .

51

. | .

Append ix P L ogistic Regression Analyses Cycling- stratif ied for p erceived degree

of u rbaniz ation

Model for cycling with all variables p<.25 included, stratified by perceived degree of urbanization

Perceived degree of urbanization = Rural

52

. | .

53

. | .

Perceived degree of urbanization = Suburban

54

. | .

55

. | .

56

. | .

Perceived degree of urbanization = Urban

57

. | .

58

. | .

59

. | .

Append ix Q Logistic Regression Analyses Cycling ( not stratif ied ) – Interaction

term includ ed

Gender

60

. | .

Age

61

. | .

Append ix R L ogistic Regression W alking- not stratif ied

Model for walking with all variables p < .25 included

62

. | .

63

. | .

64

. | .

Append ix S Logistic Regression Analyses W al king- stratif ied for perceived d egree

of u rbaniz ation

Perceived degree of urbanization = Rural

65

. | .

66

. | .

Perceived degree of urbanization = suburban

67

. | .

68

. | .

69

. | .

Perceived degree of urbanization = urban

70

. | .

71

. | .

72

. | .

Append ix T L ogistic Regression Analyses Cycling ( not stratif ied ) – interaction

term includ ed

Gender:

73

. | .

Age:

74

. | .

Append ix U Popul ation d ensity per p rovince in th e Netherl ands and origin

resp ondents

CBS, 2006

Documents

Perceived physical environmental factors related to ...essay.utwente.nl/60447/1/MA_thesis_M_Bourgondiën.pdf · transport (Cerin, Leslie & Owen, 2009 ). According to Susilo and Maat